ROLES AND RESPONSIBILITIES
- Develop, create, maintain, manage, and optimize data pipelines as workloads move from development to production for specific use cases.
- Responsible for using innovative and modern tools, techniques and architectures to partially or completely automate the most-common, repeatable and tedious data preparation and integration tasks in order to minimize manual and error-prone processes and improve productivity.
- Assist with renovating the data management infrastructure to drive automation in data integration and management.
- Develop algorithms and predictive models to solve critical business problems.
- Develop tools and libraries that will help analytics team members more efficiently interface with huge amounts of data.
- Analyze large, noisy datasets and identify meaningful patterns that provide actionable results.
- Develop and automate new enhanced imputation algorithms.
- Work with data lakes and databases including any aspect of administration or support required to maintain them
TECHNICAL COMPETENCIES (Knowledge, Skills & Abilities)
- Excellent at solving analytical problems using quantitative approaches.
- Comfort manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources
- Fluency with at least one scripting language such as Phyton and other languages like R, Java, C, C++, C# is a plus
- Strong knowledge of DevOps workflow, cloud-native platforms (containers, Kubernetes, serverless, etc.) and tools (such as Git), and infrastructure as code (IaC) tools (such as CloudFormation or Terraform)
- Strong ability to collaborate with a variety of roles and harmonize the relationship between business and IT.
- Strong passion for empirical research and for answering hard questions with data.
- Flexible analytic approach that allows for results at varying levels of precision..
- Highly self-motivated and directed.
- Keen attention to detail.
- Ability to effectively prioritize and execute tasks in a high-pressure environment
EDUCATION AND EXPERIENCE
- Bachelors degree in computer science, mathematics, or statistics
- Minimum 8 years equivalent IT work experience and 5 years in Data Engineering
- Minimum 2 years of cloud platform experience
- Experience in AI Hardware in managing and troubleshooting distributed systems like
- Apache Hadoop, spark and familiarity with Public cloud IaaS/PaaS
- Familiar with common techniques and general ML programming to ensure quality of algorithms before pushing them to production
- Experience with BI and Reporting Tools
- Experience with Data Integration tools like Spark/Databricks or equivalent
- Experience in Linux/Unix shell scripting
Job Type: Full-time
Pay: $155,000.00 - $160,000.00 per year
- Dental insurance
- Flexible spending account
- Health insurance
- Health savings account
- Paid time off
- Parental leave
- Professional development assistance
- Retirement plan
- Vision insurance
- 8 hour shift
- Monday to Friday
- Signing bonus
- Data Engineering: 8 years (Required)
- Cloud: 2 years (Required)
- Python: 5 years (Required)
Work Location: Remote
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